CountryData contains data directly provided by National
Statistics Offices (NSOs), as the focal point of the National Statistical
System (NSS). These data cover a variety of themes like poverty, education,
health and environment, agreed as priority national development indicators by
the NSS. If these data match a MDG indicator published by
an international
agency, both national and international data for that indicator are
presented side by side in the 'Comparisons' section of each country’s profile.

International
data presented in CountryData are extracted from the Global MDG database which is
managed and updated by the United Nations Statistics Division (UNSD). This
database contains indicator estimates provided by the international agencies
responsible for monitoring MDGs. The database is updated annually and is used
to produce the annual
Millennium Development Goals report. Accompanying reference metadata are based
on the Handbook for
Monitoring MDGs available for international estimates.

For a variety of reasons national and international estimates for MDG indicators
differ. Sometimes international agencies resort to their own internal estimates
of MDG indicators because of a lack of national data or dissemination
channels for national statistical indicators. Other times, agencies make
adjustments to national MDG indicator data to facilitate valid cross-country
comparisons. In many of these cases the reasons for the differences are not fully
known or understood, and this leads to confusion among users, undermines the credibility
of statistical systems, and can have serious policy implications.

MDGLabs was the first internet
platform created by the United Nations Statistics Division
(UNSD) to try to tackle differences between national and international estimates for MDGs. The
web application now displays the discrepancies between the data collected by
over 90 countries (covering Africa, Asia, Latin America and the Caribbean) and
international agencies on a specific set of 20 MDGs. CountryData incorporates
much of this website’s functionality, but goes further to streamline the
process of data exchange (i.e. through SDMX) and
concentrates on data and reference metadata availability
too. CountryData will eventually replace MDGLabs when expanded to a fuller set
of countries.

Many times the reason for differences between national and international estimates will not be obvious from the
top-level descriptions of the data (i.e. series name, sex, location, unit of
measurement etc.); therefore, more detailed textual metadata is required on
definition used, methodology adopted or how the data was obtained to understand
the exact nature of the data and determine the actual reason(s) for any
differences. This is why CountryData makes an effort to show a complete set of reference
metadata (obtained from countries also through SDMX)
and present reference metadata side by side in any comparison of national and
international estimates of the same MDG indicator.

CountryData is initially working with a small group of participants on a project funded by the UK’s Department
for International Development (DfID) to improve the collation, availability and
dissemination of national development indicators (including the MDGs). It is envisaged that over time more countries will
be included in the website. Like Mexico, a non-project country, it is possible for countries with more advanced capacity to develop their own SDMX connection with CountryData.

An SDMX registry is used to facilitate the dissemination of data in the form of SDMX messages. Structural metadata, such as Data Structure Definitions, Concepts, Codelists, etc, can be published at the registry. The registry also maintains links to data and reference metadata sources, and alerts subscribers (like CountryData) when updates are available.

The Data Structure Definition provides the design of how data exported from a
database or other source should be structured and coded in a SDMX message. Any Data Structure Definition (DSD) is
established on dimensions and attributes. Dimensions (dim) are a mandatory
requirement to identify the observation value (i.e. data point) while
attributes (att) are optional or mandatory additional descriptive or qualitative
features of the observation value.

CountryData chose to implement an expanded version of the DSD for MDG indicators (MDG DSD) for
data exchange of national development indicators with National
Statistics Offices (NSOs), because it is the most developed and
internationally recognised standard for this subject domain, i.e. the MDG DSD was
developed for the 125 diverse indicators (171 time series) collated as part of
the coordination process for MDG
progress report each year by a special Inter-Agency Expert Group (IAEG) taskforce.

The set of dimensions and attributes used to define the MDG DSD are presented in the table below:

CountryData chose to base textual metadata exchange on the MSD for MDG indicators (MDG DSD)
for data exchange of national development indicators with National
Statistics Offices (NSOs), for reasons similar to the choice of the DSD for MDGs. The set of fields used to display
the MDG MSD on CountryData are presented in the table below:

A series of steps have been built into the CountryData application to automate
the process of matching national and international estimates for comparison as
much as possible. The use of the same MDG DSD
for both the national and international series simplifies this process, and the
matching is done directly by making comparisons on key dimensions of MDG DSD, such
as series, unit of measurement, location, sex and reference area (all require
an exact match except where coded "Not Applicable"); and frequency, age group
and source type (does not require an exact match).

When two time series (national and international) are paired on the above basis then
a comparison of the associated metadata can commence. This should yield some
information on the reasons for the
differences, or further follow-up may be required with either the National
Statistics Office or International Agency provider. Any follow-up response will
be asked to be fed back through in the SDMX messages
CountryData receives, otherwise the explanation is written up in a stand alone
commentary box beside the reasons for difference categories.

CountryData presents eight categories as the main labels of comparison in the table below.
Further explanations beyond the allocation of these labels are provided where
relevant in the commentary box. This enables users to decide which data are most appropriate for
their specific purposes, and reduces the confusion surrounding different indicator estimates.

Label

Definition

No difference

Describes when there is a complete congruence between the two series, in terms of the associated observation values and years they are allocated and are available for are the same.

Discrepancy Labels

Different age groups

Describes when different age groups are used between the same time series.

Different data sources

Describes the use of results from different data sources – international agencies can use multiple data sources to compute an indicator while the country will use a single survey or an administrative source, which the agency may not have access to.

Different definitions

Describes when the international agency and the country define the indicator differently – the national definition used can be more inclusive that the specific categories included in these indicators as defined by the international agencies.

Different methodologies

Describes a different method of computation used between the country and the international agency – international agencies can use statistical models to estimate an indicator while the country will report figures directly from the survey.

Different source type

Describes when different source types are used between the same time series (i.e. admin vs. survey). “Different data sources” will also apply.

Under investigation

Applied when the data are first updated, usually a placeholder until a reason is investigated.

Unidentified

Describes following investigation, when there is a discrepancy but the reason remains unclear/ unresolved.